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Many real-world applications need to frequently access data stored on large-scale parallel disk storage systems. On one hand, prompt responses to access requests are essential for these applications. On the other hand, however, with an explosive increase of data volume and the emerging of faster disks with higher power requirements, energy consumption of disk-based storage systems has become a salient issue. To achieve energy-conservation and prompt responses simultaneously, in this paper we propose a novel energy-aware strategy, called striping-based energy-aware (SEA), which can be integrated into data placement in RAID-structured storage systems to noticeably save energy while providing quick responses. Next, to illustrate the effectiveness of SEA, we implement two SEA-powered striping-based data placement algorithms, SEA0 and SEA5, by incorporating the SEA strategy into RAID-0 and RAID-5, respectively. Extensive experimental results demonstrate that compared with traditional non-stripping data placement algorithms, our algorithms significantly improve performance and save energy. Further, compared with an existing stripping-based data placement scheme, the two SEA-powered strategies noticeably reduce energy consumption with only a little performance degradation.
Energy-aware systems, Load balancing and task assignment, Real-time distributed, Scheduling and task partitioning, Distributed applications, Real-time and embedded systems, Reliability, availability, and serviceability
Tao Xie, "SEA: A Striping-Based Energy-Aware Strategy for Data Placement in RAID-Structured Storage Systems", IEEE Transactions on Computers, vol. 57, no. , pp. 748-761, June 2008, doi:10.1109/TC.2008.27
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